Product Lead
- Identify real business problems that financial advisors face and translate them into product opportunities backed by evidence — customer interviews, workflow observation, competitive analysis, market data
- Build and maintain deep relationships with advisors to understand their daily pain points, the friction in their client relationships, and the gaps in their current technology stack
- Develop the business case for what gets built — problem sizing, competitive positioning, differentiation, and success criteria. Every feature has a "why" rooted in customer value and business impact
- Write structured product specifications that translate business needs into precise, actionable documents — your specs are the primary input to an agentic development pipeline where AI agents execute against what you write
- Own feature design and end-to-end user story creation — your user stories define the acceptance criteria that drive the team's entire test automation pipeline, from AI-generated e2e tests through regression suites
- Partner with your Tech Lead on plan review — your spec must give both humans and AI agents enough context to execute well
- Operate 6-12 weeks ahead of your team — the next three features are defined (customer problem, proposed solution, success criteria, key risks) before the current one ships
- MBA from a top-tier program and an undergraduate degree in computer science, engineering, or a related technical field
- 2+ years of product management experience at a brand-name B2B SaaS company
- Minimum 1 year as a professional software engineer — you've written production code and understand engineering from the inside
- A track record of identifying customer pain points and turning them into successful products — not just shipping features, but solving problems that drive adoption and retention
- Demonstrated ability to write detailed, structured technical specifications to drive implementation
- Strong business instincts — you think about market sizing, competitive dynamics, and customer value, not just feature lists
- Exceptional written communication
- Experience designing multi-system workflows that connect disparate data sources (support platforms, analytics, CRM, communication tools) into coherent product intelligence pipelines
- Demonstrated ability to build structured frameworks for product discovery — jobs-to-be-done analysis, opportunity scoring models, or similar systematic approaches to identifying and prioritizing customer problems
- Comfort working with LLMs as a power user — prompt engineering, agent orchestration, or building AI-assisted workflows. You don't need to train models, but you need to understand what they can and can't do well enough to design reliable agent pipelines
- Experience producing board-level or executive-facing business artifacts — investment cases, quarterly business reviews, strategy narratives — and a desire to automate the grunt work behind them
- Preferred:
- Hands-on experience with MCP (Model Context Protocol) or similar tool-integration patterns for LLMs
- Experience with workflow automation platforms (n8n, Zapier, Temporal, or custom orchestration) connecting product tooling across systems
- Background in designing feedback categorization or tagging systems — whether manual or automated
- Familiarity with AI coding tools as a user or builder
- Experience with AI/ML products, particularly conversational or agent-based systems
- Background in financial services, wealth management, or regulated industries